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The 10 Best AI Writers & Content Generators Compared

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AI Content creation tools are becoming more widely available since the development of GPT-3 (and its release through Open.ai) has made AI much more accessible.

To see just how good AI writers are, we selected 10 of the best content generators and road-tested them by comparing their output on the same topic.

We ran our own mini Turing Test while testing the AI content generators.

We asked our audience if they could tell the difference between machine and human-generated content through social media polls.

Are machines taking over the content industry? Read on and find out!

How GPT-3 Is Shaking Up Content Creation

GPT-3, the language prediction model, was introduced in May 2020 and is widely available for public use through Open AI.

The quality of GPT-3 output was a huge leap forward from GPT-2 toward asking a machine to write intelligible cohesive content.

The downside to the development of GPT-3 and vastly improved content creation tools: How do you keep pace with the output of a machine?

Google has been looking at solving the potential issues of the predicted explosion of AI content to ensure their search results don’t become swamped with low-quality content.

They recently restated that AI content is against their guidelines and updated their webmaster guidelines documentation.

How can they distinguish between a machine and just badly written human content?

The progress and development of AI writers and content tools is only just getting started.

Private investment in AI more than doubled last year to $93.5 billion in 2021.

This means that more machine learning tools are being developed that will become more integrated into the tools we use as marketers and SEO professionals.

Meta recently announced a new research project into next-generation AI.

They aim to create an AI that processes data like humans and would be indistinguishable from a human.

When that might be available is not known.

Machine domination aside, in this article, we will review a selection of the current best content creation tools to see how they compare.

And consider how they can help us do a more efficient job.

Will AI take over the content creation industry? Let’s look at the results of the tools we tested.

AI Content Creation Tools Compared

We fed all the content generator tools we tested were fed the same subject matter to generate a similar length of output.

With a meta self-referential irony, we used the simple phrase, “AI content creation.”

We compared the use of the tool and the quality of the content output. You can see that output in each of the screenshots below.

As part of the comparison, we also ran all the content through Copyscape to check for plagiarism. Only one content generator was flagged with issues.

The difference in styles was most surprising about comparing the output from all the tools.

We half expected more similar results when running the same key phrase through an AI tool, but clearly, every generator has its own variables for how content is written. Much like a variety of human writers.

Screenshot from Writesonic, May 2022AI content creation via writesonic

1. Writesonic

  • Free version up to full unlimited price plans.
  • Paid version reasonably priced.
  • 24 languages.

Writesonic is built on GPT-3 and claims the machine is trained on the content that the brands using the tool produce.

The generator is based around facilitating marketing copy, blog articles, and product descriptions. The generator can also provide content ideas and outlines and has a full suite of templates for different types of content.

We found Writesonic very easy to use and it didn’t take much work to get a full article straight out of the box.

The free plan is an option to try the basic tool with the choice to upgrade to get access to full functionality.

AI content creation via fraseScreenshot from Frase, May 2022AI content creation via frase

2. Frase

  • Paid only.
  • Cheap plans, but the credits are expensive.

Frase is a content assistant and targeted to content marketers and SEO professionals for faster and better productivity.

The tool is structured around a framework of content brief, content writing, content optimization, and content analytics.

The tool excels for research and brief outlines and the talking points tool is useful for structuring an article. A content brief can be prepared in minutes.

For content writing, the generator doesn’t produce a full article straight out of the box, and it needs some work to get the results. But, the quality of content output is high.

Frase is a useful tool for content marketers that can help to reduce the amount of time spent on writing with a competent writer in charge.

Copy.ai content creationScreenshot from Copy.ai, May 2022Copy.ai content creation

3. Copy.ai

  • Free plan and paid unlimited.
  • Paid plans very cheap.
  • 25 languages.

Designed to be an antidote to writer’s block, Copy.ai is a cheap and easy-to-use content generator.

Copy.ai provides templates across various content types such as blogs, ads, sales, websites, and social media. The generator also provides translation into 25 languages.

An unusual addition to their range of tools includes a baby name generator, but we didn’t manage to get any usable results for a baby name.

Although easy to use, it’s a tool for anyone producing volume content up to an average level but not for high-end content production.

The free plan is an option to try before you buy.

AI content creation via AI WriterScreenshot from AI Writer, May 2022AI content creation via AI Writer

4. AI Writer

  • Free trial and paid plans.
  • Flagged in plagiarism checks.

AI Writer pitches itself as SEO-friendly, producing fresh and relevant copy that can save you 50% of your writing time.

From our test, AI Writer is an easy tool to use, and you get an article written within minutes.

However, it was the only tool we tested that our Copyscape plagiarism check flagged.

The articles from the writer were not the most fluid or cohesive, and felt much like an article spinner.

Out of all content generators tested, this tool didn’t feel like it was at the same standard of output as the others.

Hyperwrite toolScreenshot from Hyperwrite, May 2022Hyperwrite tool

5. Hyperwrite

Hyperwrite’s claim is to use the most advanced AI generator. It’s one of the most basic tools to use and generate content and the only tool that is fully free to use.

From our test, we found the output to be surprisingly cohesive and fluid.

A useful part of the tool is that it can rewrite a sentence or make paragraphs longer to quickly restructure and build out content where needed.

The text output from Hyperwrite was the one that most people chose as being human written in our Turing Test on social media.

It’s also a free tool that offers some of the better quality of all the tools compared and is the perfect tool to test the ability and constraints of AI content generation.

INK toolScreenshot from INK, May 2022INK tool

6. INK

  • Free version and full paid plans.
  • Chrome extension.

INK is another AI-powered tool targeted at content marketers and SEO experts as a content assistant for faster output and optimized content.

INK has 60 templates based around advertising, growth, website, and writing, including YouTube, pain agitation, catchy subjects, and listicles.

There’s a focus on SEO and getting content to rank with tools that support optimization and a tool scoring system to rate how well your article is optimized.

In the hands of a professional writer, INK can be a useful tool to support output, but it won’t do the job for you.

The tool took some work to get the final output, which was sometimes questionable.

INK generously offers up to 10 articles free in a month, which provides plenty of scope to try before you buy.

Rytr AI Content generationScreenshot from Rytr, May 2022Rytr AI Content generation

7. Rytr

  • Free plan to unlimited plan.
  • Cheap price plans.
  • 30 languages.

Rytr is a full AI content generation tool built on GPT-3, emphasizing generating content that converts.

The tool has over 30 templates for marketing copy, blogs, and product descriptions. It also incorporates AIDA and PAS formulas to get the best results for copywriting.

The tool was quick and easy to use and we had a reasonable quality article in five minutes.

Rytr has a free plan with access to all the tools with a limit of 5,000 characters a month. The paid plans start very cheap if you want to progress and take more advantage of the tool.

Smart Copy toolScreenshot from Smart Copy, May 2022Smart Copy tool

8. Snazzy (Now Smart Copy By Unbounce)

  • Free plan to paid unlimited version.

Snazzy is powered by GPT-3 and their own proprietary machine learning to create a tool focused on landing page generation.

Unbounce acquired Snazzy and rebranded as Smart Copy and is now structured to complement and support Unbounce for seamless landing page creation.

A full range of tools are available, such as outlines, ad copy, product descriptions, and social media copy. But, the tool is pitched toward generating sales-led persuasion copy.

The results generated in our test for ‘AI content generation’ were somewhat unpredictable and not intelligible enough for an article. However, we didn’t test specifically for landing page copy.

Snazzy/Smart Copy offers a free plan with up to five credits a day to try to see if it works for you.

Long Shot toolScreenshot from Long Shot, May 2022Long Shot tool

9. Long Shot

  • Free version up to unlimited version.
  • Eight Languages.

Long shot pitches itself as an AI-powered long-form content assistant to produce SEO-friendly content built on a combination of GPT-3 and custom AI models.

It includes over 30 tools for keyword research, rephrasing, and fact-checking, and you can write in eight languages.

From our test, we found Long Shot easy to use to produce reasonable quality content.

One interesting point: When comparing all the content output from the range of tools we tested, this was the only generator that included any brand names such as Google’s RankBrain and Buzzsumo.

This detail made the content output quite believable that it could be human-written.

Long Shot offers a free plan with up to 10 credits a day.

Jasper content toolScreenshot from Jasper, May 2022Jasper content tool

10. Jasper

  • Paid plans only.
  • 25 languages.

Jasper (previously Jarvis) claims it will help you write faster, beat writer’s block, and rank better with SEO-optimized content.

They also claim to have consulted with SEO professionals and direct marketing experts to perfect how the AI generator writes content.

Jasper has over 50 templates for producing content, including AIDA, PAS, blogs, social media, and marketing.

From our experience, Jasper is another writing support tool and not one that writes full articles without input. With guidance, the content generated from the tool is very good.

The tool is easy to use and the quality was good; however, we found the content generated was limited to short articles.

Jasper doesn’t offer any free plans, but it offers a free trial for five days.

Be aware you have to input your credit card and you will get charged if you forget to cancel.

Packages are not cheap, so you would have to max out the five-day trial to see if it was worth the investment.

The Results Of Our AI Content Turing Test

The test we ran was a simple short poll to gauge opinion and not a statistically significant result of large numbers. But, the results we found and the comments were surprising.

The 10 Best AI Writers & Content Generators ComparedThe 10 Best AI Writers & Content Generators Compared

The 10 Best AI Writers & Content Generators ComparedThe 10 Best AI Writers & Content Generators Compared

The 10 Best AI Writers & Content Generators ComparedThe 10 Best AI Writers & Content Generators Compared

The 10 Best AI Writers & Content Generators ComparedThe 10 Best AI Writers & Content Generators Compared

We provided three examples of 100 words of content, all based on “AI content creation” and created from some of the tools above. We wrote the fourth snippet.

We asked our audience, “Can you tell which one is human-generated?”

The short result is that no one could distinguish between AI-generated content and the human-written paragraph.

The reasons that people offered to justify those (incorrect) choices were quite interesting:

comparing AI generated content vs. humanImage from Twitter, May 2022comparing AI generated content vs. human
comparing AI generated content vs. humanImage from Twitter, May 2022comparing AI generated content vs. human
comparing AI generated content vs. humanImage from Twitter, May 2022comparing AI generated content vs. human

Out of all the comments, only a few guessed that number 4 was the human-generated copy:

comparing AI generated content vs. humanImage from Twitter, May 2022comparing AI generated content vs. human
comparing AI generated content vs. humanImage from Twitter, May 2022comparing AI generated content vs. human
comparing AI generated content vs. humanImage from Twitter, May 2022comparing AI generated content vs. human

See the full Twitter thread here.

From all responses across Twitter, Facebook, and LinkedIn, most people thought that number 1 was the human-written text.

The second text had the least amount of responses. Not surprising as this was not the best quality snippet of generated content.

The actual human-generated text was number 4 and came in third place in votes.

How You Can Use AI In Content Marketing

There’s a lot of experimentation happening with GPT-3 with plenty of fun tools being produced. But, look past these novelty applications to see where they can really have an impact.

Yes, you can machine generate your Twitter feed, but social media is about interaction and engagement.

Yes, you can write an article, but is it good enough to put your name to or represent your brand?

What needs to be considered with AI content generation is that a tool is only as good as the person operating it.

They are excellent for productivity and speeding up content production. But, you need someone who knows their subject and is a good writer behind the wheel to get results worthy of using.

A content marketer can take advantage of AI as an efficiency tool to make repetitive tasks easier and output faster.

In those terms, AI will become more and more seamlessly integrated into marketing.

Where AI Content Does Work

  • For product descriptions at scale.
  • For meta descriptions at scale.
  • Sports results broadcasting.
  • To support a writer’s productivity.

Where AI Content Doesn’t Work

  • Producing well-researched content.
  • Creating data-driven content.
  • Having innovative and fresh ideas.
  • Thought leadership.

Will AI Take Over Content Creation?

Although it’s now almost impossible to tell the difference between human and machine-generated content, the level of that content won’t win any journalist awards.

A tool cannot make up for a lack of knowledge or ability. It can only enhance it.

The machine generates content output from what is input; therefore, it only regurgitates; it isn’t creating new ideas.

It’s ideal for some tasks, but not for high-level well-researched content or thought leadership. And this is where good researchers and writers will become more valuable.

You can be assured that content creation will go into overdrive with AI.

You can also be assured that good quality journalist standard content with unique data, thought opinions, and insights will become the only way to get visibility and sustain an audience.

Who’s the winner of that game?

More resources: 


Featured Image: ProStockStudio/Shutterstock

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What Is Schema Markup & Why Is It Important For SEO?

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What Is Schema Markup & Why Is It Important For SEO?

Schema.org is a collection of vocabulary (or schemas) used to apply structured data markup to web pages and content. Correctly applying schema can improve SEO outcomes through rich snippets.

Structured data markup is translated by platforms such as Google and Microsoft to provide enhanced rich results (or rich snippets) in search engine results pages or emails. For example, you can markup your ecommerce product pages with variants schema to help Google understand product variations.

Schema.org is an independent project that has helped establish structured data consistency across the internet. It began collaborating with search engines such as Google, Yahoo, Bing, and Yandex back in 2011.

The Schema vocabulary can be applied to pages through encodings such as RDFa, Microdata, and JSON-LD. JSON-LD schema is preferred by Google as it is the easiest to apply and maintain.

Schema is not a ranking factor.

However, your webpage becomes eligible for rich snippets in SERPs only when you use schema markup. This can enhance your search visibility and increase CTR on your webpage from search results.

Schema can also be used to build a knowledge graph of entities and topics. Using semantic markup in this way aligns your website with how AI algorithms categorize entities, assisting search engines in understanding your website and content.

This means that search engines should have additional information to help them figure out what the webpage is about.

You can even link your entities directly to sites like Wikipedia or Google’s knowledge graph to build explicit connections. Using Schema this way can have positive SEO results, according to Martha van Berkel, CEO of Schema App:

By helping search engines understand content, you are assisting them in saving resources (especially important when you have a large website with millions of pages) and increasing the chances for your content to be interpreted properly and ranked well. While this may not be a ranking factor directly, Schema helps your SEO efforts by giving search engines the best chance of interpreting your content correctly, giving users the best chance of discovering it.

Listed above are some of the most popular uses of schema, which are supported by Google and other search engines.

You may have an object type that has a schema.org definition but is not supported by search engines.

In such cases, it is advised to implement them, as search engines may start supporting them in the future, and you may benefit from them as you already have that implementation.

Google recommends JSON-LD as the preferred format for structured data. Microdata is still supported, but JSON-LD schema is recommended.

In certain circumstances, it isn’t possible to implement JSON-LD schema due to website technical infrastructure limitations such as old content management systems). In these cases, the only option is to markup HTML via Microdata or RDFa.

You can now mix JSON-LD and Microdata formats by matching the @id attribute of JSON-LD schema with the itemid attribute of Microdata schema. This approach helps reduce the HTML size of your pages.

For example, in a FAQ section with extensive text, you can use Microdata for the content and JSON-LD for the structured data without duplicating the text, thus avoiding an increase in page size. We will dive deeper into this below in the article when discussing each type in detail.

JSON-LD encodes data using JSON, making it easy to integrate structured data into web pages. JSON-LD allows connecting different schema types using a graph with @ids, improving data integration and reducing redundancy.

Let’s look at an example. Let’s say that you own a store that sells high-quality routers. If you were to look at the source code of your homepage, you would likely see something like this:

Once you dive into the code, you’ll want to find the portion of your webpage that discusses what your business offers. In this example, that data can be found between the two

tags.

The following JSON-LD formatted text will markup the information within that HTML fragment on your webpage, which you may want to include in your webpage’s

section.



This snippet of code defines your business as a store via the attribute"@type": "Store".

Then, it details its location, contact information, hours of operation from Monday to Saturday, and different operational hours for Sunday.

By structuring your webpage data this way, you provide critical information directly to search engines, which can improve how they index and display your site in search results. Just like adding tags in the initial HTML, inserting this JSON-LD script tells search engines specific aspects of your business.

Let’s review another example of WebPage schema connected with Organization and Author schemas via @id. JSON-LD is the format Google recommends and other search engines because it’s extremely flexible, and this is a great example.



In the example:

  • Website links to the organization as the publisher with @id.
  • The organization is described with detailed properties.
  • WebPage links to the WebSite with isPartOf.
  • NewsArticle links to the WebPage with isPartOf, and back to the WebPage with mainEntityOfPage, and includes the author property via @id.

You can see how graph nodes are linked to each other using the"@id"attribute. This way, we inform Google that it is a webpage published by the publisher described in the schema.

The use of hashes (#) for IDs is optional. You should only ensure that different schema types don’t have the same ID by accident. Adding custom hashes (#) can be helpful, as it provides an extra layer of insurance that they will not be repeated.

You may wonder why we use"@id"to connect graph nodes. Can’t we just drop organization, author, and webpage schemas separately on the same page, and it is intuitive that those are connected?

The issue is that Google and other search engines cannot reliably interpret these connections unless explicitly linked using @id.

Adding to the graph additional schema types is as easy as constructing Lego bricks. Say we want to add an image to the schema:

{
   "@type": "ImageObject",
   "@id": "https://www.example.com/#post-image",
   "url": "https://www.example.com/example.png",
   "contentUrl": "https://www.example.com/example.png",
   "width": 2160,
   "height": 1215,
   "thumbnail": [
     {
        "@type": "ImageObject",
        "url": "https://example.com/4x3/photo.jpg",
        "width": 1620,
        "height": 1215
      },
      {
        "@type": "ImageObject",
        "url": "https://example.com/16x9/photo.jpg",
        "width": 1440,
        "height": 810
      },
      {
        "@type": "ImageObject",
        "url": "https://example.com/1x1/photo.jpg",
        "width": 1000,
        "height": 1000
      }
    ]
}

As you already know from the NewsArticle schema, you need to add it to the above schema graph as a parent node and link via @id.

As you do that, it will have this structure:



Quite easy, isn’t it? Now that you understand the main principle, you can build your own schema based on the content you have on your website.

And since we live in the age of AI, you may also want to use ChatGPT or other chatbots to help you build any schema you want.

2. Microdata Schema Format

Microdata is a set of tags that aims to make annotating HTML elements with machine-readable tags much easier.

However, the one downside to using Microdata is that you have to mark every individual item within the body of your webpage. As you can imagine, this can quickly get messy.

Take a look at this sample HTML code, which corresponds to the above JSON schema with NewsArticle:

Our Company

Example Company, also known as Example Co., is a leading innovator in the tech industry.

Founded in 2000, we have grown to a team of 200 dedicated employees.

Our slogan is: "Innovation at its best".

Contact us at +1-800-555-1212 for customer service.

Our Founder

Our founder, Jane Smith, is a pioneer in the tech industry.

Connect with Jane on Twitter and LinkedIn.

About Us

This is the About Us page for Example Company.

Example News Headline

This is an example news article.

This is the full content of the example news article. It provides detailed information about the news event or topic covered in the article.

Author: John Doe. Connect with John on Twitter and LinkedIn.

If we convert the above JSON-LD schema into Microdata format, it will look like this:

Our Company

Example Company, also known as Example Co., is a leading innovator in the tech industry.

Founded in 2000-01-01, we have grown to a team of 200 dedicated employees.

Our slogan is: Innovation at its best.

Contact us at +1-800-555-1212 for Customer Service.

Example Company Logo

Connect with us on: Facebook, Twitter, LinkedIn

Our Founder

Our founder, Jane Smith, is a pioneer in the tech industry.

Connect with Jane on Twitter and LinkedIn.

About Us

This is the About Us page for Example Company.

Example News Headline

This is an example news article.

This is the full content of the example news article. It provides detailed information about the news event or topic covered in the article.

Author:

Example image

This example shows how complicated it becomes compared to JSON-LD since the markup is spread over HTML. Let’s understand what is in the markup.

You can see

tags like:


By adding this tag, we’re stating that the HTML code contained between the

blocks identifies a specific item.

Next, we have to identify what that item is by using the ‘itemtype’ attribute to identify the type of item (Person).


An item type comes in the form of a URL (such as https://schema.org/Person). Let’s say, for example, you have a product you may use http://schema.org/Product.

To make things easier, you can browse a list of item types here and view extensions to identify the specific entity you’re looking for. Keep in mind that this list is not all-encompassing but only includes ones that are supported by Google, so there is a possibility that you won’t find the item type for your specific niche.

It may look complicated, but Schema.org provides examples of how to use the different item types so you can see what the code is supposed to do.

Don’t worry; you won’t be left out in the cold trying to figure this out on your own!

If you’re still feeling a little intimidated by the code, Google’s Structured Data Markup Helper makes it super easy to tag your webpages.

To use this amazing tool, just select your item type, paste in the URL of the target page or the content you want to target, and then highlight the different elements so that you can tag them.

3. RDFa Schema Format

RDFa is an acronym for Resource Description Framework in Attributes. Essentially, RDFa is an extension to HTML5 designed to aid users in marking up structured data.

RDFa isn’t much different from Microdata. RDFa tags incorporate the preexisting HTML code in the body of your webpage. For familiarity, we’ll look at the same code above.

The HTML for the same JSON-LD news article will look like:

vocab="https://schema.org/" typeof="WebSite" resource="https://www.example.com/#website">

Our Company

Example Company, also known as Example Co., is a leading innovator in the tech industry.

Founded in 2000-01-01, we have grown to a team of 200 dedicated employees.

Our slogan is: Innovation at its best.

Contact us at +1-800-555-1212 for Customer Service.

https://www.example.com Example Company Logo

Connect with us on: Facebook, Twitter, LinkedIn

Our Founder

Our founder, Jane Smith, is a pioneer in the tech industry.

Connect with Jane on Twitter and LinkedIn.

About Us

This is the About Us page for Example Company.

https://www.example.com/about

Example News Headline

This is an example news article.

This is the full content of the example news article. It provides detailed information about the news event or topic covered in the article.

Author: John Doe Profile Twitter LinkedIn

Example image

Unlike Microdata, which uses a URL to identify types, RDFa uses one or more words to classify types.

vocab=”http://schema.org/” typeof=”WebPage”>

If you wish to identify a property further, use the ‘typeof’ attribute.

Let’s compare JSON-LD, Microdata, and RDFa side by side. The @type attribute of JSON-LD is equivalent to the itemtype attribute of Microdata format and the typeof attribute in RDFa. Furthermore, the propertyName of JSON-LD attribute would be the equivalent of the itemprop and property attributes.

Attribute Name JSON-LD Microdata RDFa
Type @type itemtype typeof
ID @id itemid resource
Property propertyName itemprop property
Name name itemprop=”name” property=”name”
Description description itemprop=”description” property=”description”

For further explanation, you can visit Schema.org to check lists and view examples. You can find which kinds of elements are defined as properties and which are defined as types.

To help, every page on Schema.org provides examples of how to apply tags properly. Of course, you can also fall back on Google’s Structured Data Testing Tool.

4. Mixing Different Formats Of Structured Data With JSON-LD

If you use JSON-LD schema but certain parts of pages aren’t compatible with it, you can mix schema formats by linking them via @id.

For example, if you have live blogging on the website and a JSON-LD schema, including all live blogging items in the JSON schema would mean having the same content twice on the page, which may increase HTML size and affect First Contentful Paint and Largest Contentful Paint page speed metrics.

You can solve this either by generating JSON-LD dynamically with JavaScript when the page loads or by marking up HTML tags of live blogging via the Microdata format, then linking to your JSON-LD schema in the head section via “@id“.

Here is an example of how to do it.

Say we have this HTML with Microdata markup with itemid="https://www.example.com/live-blog-page/#live-blog"

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We can link to it from the sample JSON-LD example we had like this:



If you copy and paste HTML and JSON examples underneath in the schema validator tool, you will see that they are validating properly.

The schema validator does validate the above example.The schema validator does validate the above example.

The SEO Impact Of Structured Data

This article explored the different schema encoding types and all the nuances regarding structured data implementation.

Schema is much easier to apply than it seems, and it’s a best practice you must incorporate into your webpages. While you won’t receive a direct boost in your SEO rankings for implementing Schema, it can:

  • Make your pages eligible to appear in rich results.
  • Ensure your pages get seen by the right users more often.
  • Avoid confusion and ambiguity.

The work may seem tedious. However, given time and effort, properly implementing Schema markup is good for your website and can lead to better user journeys through the accuracy of information you’re supplying to search engines.


Image Credits

Featured Image: Paulo Bobita
Screenshot taken by author

 

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Looking for a Content Marketing Solution to Increase Traffic and Revenue? I’m the founder of Measurable SEO and former COO ...

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Gen Z Ditches Google, Turns To Reddit For Product Searches

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In this photo illustration, the Reddit logo is displayed on a smartphone screen.

A new report from Reddit, in collaboration with GWI and AmbassCo, sheds light on the evolving search behaviors of Generation Z consumers.

The study surveyed over 3,000 internet users across the UK, US, and Germany, highlighting significant changes in how young people discover and research products online.

Here’s an overview of key findings and the implications for marketers.

Decline In Traditional Search

The study found that Gen Z uses search engines to find new brands and products less often.

That’s because they shop online differently. They’re less interested in looking for expert reviews or spending much time searching for products.

There are also frustrations with mobile-friendliness and complex interfaces on traditional search platforms.

Because of this, traditional SEO strategies might not work well for reaching younger customers.

Takeaway

Companies trying to reach Gen Z might need to try new methods instead of just focusing on being visible on Google and other search engines.

Rise Of Social Media Discovery

Screenshot from Reddit study titled: “From search to research: How search marketers can keep up with Gen Z.”, June 2024.

Gen Z is increasingly using social media to find new brands and products.

The study shows that Gen Z has used social media for product discovery 36% more frequently since 2018.

This change is affecting how young people shop online. Instead of searching for products, they expect brands to appear in their social media feeds.

1719123963 547 Gen Z Ditches Google Turns To Reddit For Product SearchesScreenshot from Reddit study titled: “From search to research: How search marketers can keep up with Gen Z.”, June 2024.

Because of this, companies trying to reach young customers need to pay more attention to how they present themselves on social media.

Takeaway

To succeed at marketing to Gen Z, businesses will likely need to focus on two main things:

  1. Ensure that your content appears more often in social media feeds.
  2. Create posts people want to share and interact with.

Trust Issues With Influencer Marketing

Even though more people are finding products through social media, the report shows that Gen Z is less likely to trust what social media influencers recommend.

These young shoppers often don’t believe in posts that influencers are paid to make or products they promote.

Instead, they prefer to get information from sources that feel more real and are driven by regular people in online communities.

Takeaway

Because of this lack of trust, companies must focus on being genuine and building trust when they try to get their websites to appear in search results or create ads.

Some good ways to connect with these young consumers might be to use content created by regular users, encourage honest product reviews, and create authentic conversations within online communities.

Challenges With Current Search Experiences

The research shows that many people are unhappy with how search engines work right now.

More than 60% of those surveyed want search results to be more trustworthy. Almost half of users don’t like looking through many search result pages.

Gen Z is particularly bothered by inaccurate information and unreliable reviews.

1719123963 785 Gen Z Ditches Google Turns To Reddit For Product SearchesScreenshot from Reddit study titled: “From search to research: How search marketers can keep up with Gen Z.”, June 2024.

Takeaway

Given the frustration with search quality, marketers should prioritize creating accurate, trustworthy content.

This can help build brand credibility, leading to more direct visits.

Reddit: A Trusted Alternative

The report suggests that Gen Z trusts Reddit when looking up products—it’s their third most trusted source, after friends and family and review websites.

1719123963 403 Gen Z Ditches Google Turns To Reddit For Product SearchesScreenshot from Reddit study titled: “From search to research: How search marketers can keep up with Gen Z.”, June 2024.

Young users like Reddit because it’s community-based and provides specific answers to users’ questions, making it feel more real.

It’s worth noting that this report comes from Reddit itself, which probably influenced why it’s suggesting its own platform.

Takeaway

Companies should focus more on being part of smaller, specific online groups frequented by Gen Z.

That could include Reddit or any other forum.

Why SEJ Cares

As young people change how they look for information online, this study gives businesses important clues about connecting with future customers.

Here’s what to remember:

  • Traditional search engine use is declining among Gen Z.
  • Social media is increasingly vital for product discovery.
  • There’s growing skepticism towards influencer marketing.
  • Current search experiences often fail to meet user expectations.
  • Community-based platforms like Reddit are gaining trust.

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Google Clarifies Organization Merchant Returns Structured Data

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Google updates organization structured data for merchant returns

Google quietly updated their organization structured data documentation in order to clarify two points about merchant returns in response to feedback about an ambiguity in the previous version.

Organization Structured Data and Merchant Returns

Google recently expanded their Organization structured data so that it could now accommodate a merchant return policy. The change added support for adding a sitewide merchant return policy.

The original reason for adding this support:

“Adding support for Organization-level return policies

What: Added documentation on how to specify a general return policy for an Organization as a whole.

Why: This makes it easier to define and maintain general return policies for an entire site.”

However that change left unanswered about what will happen if a site has a sitewide return policy but also has a different policy for individual products.

The clarification applies for the specific scenario of when a site uses both a sitewide return policy in their structured data and another one for specific products.

What Takes Precedence?

What happens if a merchant uses both a sitewide and product return structured data? Google’s new documentation states that Google will ignore the sitewide product return policy in favor of a more granular product-level policy in the structured data.

The clarification states:

“If you choose to provide both organization-level and product-level return policy markup, Google defaults to the product-level return policy markup.”

Change Reflected Elsewhere

Google also updated the documentation to reflect the scenario of the use of two levels of merchant return policies in another section that discusses whether structured data or merchant feed data takes precedence. There is no change to the policy, merchant center data still takes precedence.

This is the old documentation:

“If you choose to use both markup and settings in Merchant Center, Google will only use the information provided in Merchant Center for any products submitted in your Merchant Center product feeds, including automated feeds.”

This is the same section but updated with additional wording:

“If you choose to use both markup (whether at the organization-level or product-level, or both) and settings in Merchant Center, Google will only use the information provided in Merchant Center for any products submitted in your Merchant Center product feeds, including automated feeds.”

Read the newly updated Organization structured data documentation:

Organization (Organization) structured data – MerchantReturnPolicy

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